Abstract
This paper presents design considerations of an Extended Kalman Filter (EKF) based Wireless Sensor Network (WSN) aided indoor localization for unmanned vehicles (UV). In this approach, we integrate Received Signal Strength Indicator (RSSI) measurements into an EKF based localization system. The localization system primarily uses measurements from a Laser Range Finder (LRF) and keeps track of the current position of the UV using an EKF-based algorithm. The integration of RSSI measurements at predetermined intervals improves the accuracy of the localization system. It may also prevent large drifts from the ground truth, kidnapping, and loop closure errors. Player/Stage based simulation studies were conducted to prove the effectiveness of the proposed system. The results of the comparative simulations show that integrating RSSI measurements into the localization system improves the system’s accuracy.
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Tuna, G., Altun, Y., Mumcu, T.V., Gulez, K. (2012). WSN Aided Indoor Localization for Unmanned Vehicles. In: Huang, DS., Ma, J., Jo, KH., Gromiha, M.M. (eds) Intelligent Computing Theories and Applications. ICIC 2012. Lecture Notes in Computer Science(), vol 7390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31576-3_67
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DOI: https://doi.org/10.1007/978-3-642-31576-3_67
Publisher Name: Springer, Berlin, Heidelberg
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